See how Willow can help you cut costs, save energy, and operate your buildings more efficiently and sustainably.
Modern buildings depend on a sophisticated blend of Operational Technology (OT) and Information Technology (IT) systems to deliver operational efficiency. These systems range from HVAC units and electrical to plumbing and lighting. Managing them separately across organization boundaries creates silos that hinder collaboration and limit holistic insights.
Willow makes unifying IT and OT easy. By bringing together data from multiple systems into a digital twin and applying Operational AI, organizations can unlock powerful, real-time analytics that drive smarter decision-making. Operational AI enables a journey that starts with intelligent energy optimization, progresses towards enhanced occupant comfort and grid-aware energy load management, all while reducing operational costs and environmental impact.
Willow’s Activate Packs are structured to support the evolution towards creating a world where buildings respond to the people, purpose and environments they serve.
As part of onboarding with Willow, the Deployment & Activation team creates a digital twin of the building by integrating data from OT and IT systems. This enables facility teams to visualize, map, and monitor all components and states of a building or campus. This comprehensive data collection reveals previously invisible relationships and unlocks new insights. Applying AI analytics to optimize energy and operational performance allows teams to monitor system health, receive alerts, and take informed actions. With these analytics activated, facility teams can enhance operations by detecting faults, conducting design-based analysis, applying dynamic baselines, adjusting for occupancy, and optimizing for grid awareness.
Let’s walk through each of the five key stages in this journey:
Willow transforms building operations by turning system data into actionable insights. Skills run 24/7 to ensure equipment is running optimally and to spec. Insights help identify inefficiencies that can affect energy usage, occupant comfort, and operational costs. By assigning impact scores and metrics, the platform enables users to prioritize issues that have the highest avoidable cost and accelerates troubleshooting through targeted diagnostics.
As an example, a skill called AHU Cooling Coil Open with Low Temp Drop runs on a Roof Top Unit and finds failing diagnostics.
Facility teams receive an insight notification and run Willow Copilot to quickly understand what the diagnostics mean and move towards identifying the root cause.
Willow ensures that inefficiencies don’t go unnoticed. Users gain clarity and guidance on root cause and corrective actions. This avoids the common pitfall of addressing superficial symptoms which can result in sending out technicians repeatedly to address the same underlying problem.
Willow runs Skills that leverage the design specification of equipment installed. An example Skill is Cooling Coil Leaving Air Temperature Exceeds Design Spec, which compares the real-time Leaving Air Temperature as measured by a sensor, 14 deg C to the Design Value of 12 deg C specified in the design docs. By using AI techniques to pull in static data from design drawings, Willow hydrates asset twin properties in the Knowledge Graph. As a result, static data can be compared against live data to know when systems are operating outside spec as designed by the equipment manufacturer.
Resolving a design-spec insight can lead to reduced energy consumption, lower operational costs, and improved system efficiency. Occupant comfort is improved by meeting temperature and ventilation standards and equipment lifespan may be extended.
The concept of a Dynamic Baseline refers to the ability to continuously adjust to “normal” system behavior. Instead of relying on fixed thresholds, it identifies deviations from expected behavior. Willow uses historical data to identify anomalies based on past system performance under similar load conditions. This enhances early detection and visibility into system performance.
As an example, water leak detection insights in Willow are generated when telemetry from water-use assets such as sensors on pipes, tanks, or plumbing fixtures shows abnormal activity that may indicate a leak. Data sources like flow sensors and moisture detectors provide real-time usage and alert data. Insights are triggered either by threshold-based rules as per design spec or more advanced dynamic baseline rules, which learn and adapt to normal usage patterns over time. This approach accounts for seasonal shifts, occupancy changes, and scheduled water use, enabling more accurate leak detection, fewer false alarms, and faster, context-rich interventions that help prevent damage and reduce costs.
Willow enables organizations to combine multiple occupancy signals such as building access control with badge swipe data, people counting sensors, and environmental motion detectors. Each signal type offers unique context: access control shows entry and exit events, people counters track real-time presence, and motion sensors detect activity. When these are integrated, the system can cross-validate data, reduce false positives, and build a more reliable picture of space utilization.
Occupancy data enables Active Control. During unoccupied periods, building systems like HVAC can automatically scale down, reducing unnecessary energy use. Conversely, when occupancy is detected or predicted, systems can preemptively adjust to ensure comfort. This real-time responsiveness leads to cost savings by minimizing energy waste and optimizing equipment runtime.
Willow can leverage real-time data from the grid’s carbon intensity and on-site assets to generate actionable insights that help shape or shift energy usage. By analyzing when the grid is cleaner (lower carbon mix) or more expensive (peak pricing), Willow can recommend optimal times to run high-energy systems or defer non-critical loads. This dynamic approach enables facility teams to reduce operational costs and carbon emissions. For example, energy-intensive processes can be scheduled during periods of low carbon intensity, while on-site renewables can be prioritized when grid conditions are at peak pricing. The result is smarter energy management that aligns with both financial and sustainability goals.
The journey through Willow’s insights spectrum creates a powerful, data-driven framework for optimized building operations. Each step enhances system visibility, contextualizes performance, and enables adaptive control. By integrating fault detection, design validation, and dynamic modeling with real-time occupancy and grid carbon data, Willow empowers facility teams to lower operational costs and achieve sustainability goals with precision and confidence.